- #Simulate serialization in one single call
- binarize(data_ascii, data_bin_file, 500, ",", nbytes, endian)
- expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8)
- for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
- {
- data_lines = getDataInFile(indices, data_bin_file, nbytes, endian)
- expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6)
- }
- unlink(data_bin_file)
-
- #...in several calls (last call complete, next call NULL)
- for (i in 1:20)
- binarize(data_ascii[((i-1)*10+1):(i*10),], data_bin_file, 20, ",", nbytes, endian)
- expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8)
- for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
- {
- data_lines = getDataInFile(indices, data_bin_file, nbytes, endian)
- expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6)
- }
- unlink(data_bin_file)
+ # Now with a random matrix, compare with (trusted) R version
+ series = matrix(runif(n*L, min=-7, max=7), nrow=L)
+ mi = epclust:::.computeMedoidsIndices(medoids, series)
+ mi_ref = R_computeMedoidsIndices(medoids, series)
+ expect_equal(mi, mi_ref)